It is important for image scanning and other document reproduction systems to be able to scan a document and accurately determine the color of each pixel of the scanned image. This is important for determining edge transitions. Edge detection is also important to research involving computer vision and feature extraction.
One goal of edge detection is to mark the points in an image at which the intensity changes sharply. A typical edge might be for instance a border between a block of red color and a block of yellow. Whereas, a line may be a small number of pixels of a different color on an otherwise unchanging background. There will be one edge on each side of the line.
Problems may also arise with false detection associated with color fringing. In optics, for example, chromatic aberration may be caused by a lens having a different refractive index for different wavelengths of light. The term “purple fringing” is used in the photographic arts. Longitudinal and lateral chromatic aberration of a lens is seen as “fringes” of color around the image, because each color in the optical spectrum cannot be focused at a single common point on the optical axis. Similar colored fringing around highlights may also be caused by lens flare. Colored fringing around highlights or dark regions may be due to the receptors for different colors having differing dynamic ranges or sensitivities.
In a color scanning and multifunction system, in order to achieve high output image quality it is often important have a good neutral pixel detection function in the image path. One of the challenges in neutral pixel detection is to differentiate pixels which are originally neutral but have some off-neutral chrominance values due to factors such as color space conversion error from low chroma color pixels such as the ones in highlight halftone regions. As with other image segmentation and analysis functions, neutral pixel detection has challenges related to improving robustness of neutral pixel detection such that the problem of missing or false detection is reduced.
Another challenge in neutral pixel detection is the need to deal with possible color mis-registration introduced in the scanning process. Mis-registration of RGB planes would cause otherwise neutral edges to have off-neutral values.
Accordingly, what is needed in this art are increasingly sophisticated methods for neutral pixel detection in an image path of a xerographic, color scanning, or other multi-function color reproduction system which reduce the aforementioned problems associated with pixel based neutral detection.